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GPU
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DigitalOcean
SAP BASIS
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Internal Communications
IC
Integrated Circuit
Roadmaps
IT Strategy
Benchmarking
Innovation
Marketing Intelligence
MI
Assembly
Fusion
Transformer
RMS
Routers
Generalized Linear Model
Stacks Blockchain
Procurement
System Integration
Art
Mentorship
Design Review
Management
Collaboration
Product Management
Performance Tuning
High Performance Computing
Generative Artificial Intelligence (AI)
Parallel Computing
Computer Hardware
Fluency
Open Source
Systems Design
Optimization
Leadership
IT Management
Delegation
GPU
Scheduling
Value Engineering
CUDA
Cloud Computing
Artificial Intelligence
Organizational Development
Training
LinkedIn
Market Analysis
DigitalOcean
SAP BASIS
Military

Summary

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together-while learning, having fun, and making a profound difference for the dreamers and builders in the world.

DigitalOcean is seeking a Senior Engineer 2 to play a key technical role in our AI Inference Optimization team. DigitalOcean aims to be the Inference Cloud of choice for digitally native companies and you will help ensure we can offer the industry-leading performance for our inference services. You will be responsible for the architectural decisions that maximize throughput and minimize latency for the world's most advanced large models. As an IC leader, you will act as a force multiplier for the engineering organization, solving the most complex bottlenecks in memory bandwidth and compute utilization while guiding the technical roadmap for our high-performance inference fleet.
What You'll Do:

Performance Architecture: Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers, ensuring our infrastructure extracts maximum value from every TFLOP.
Deep-Dive Optimization: Engineer solutions for complex performance issues, including attention layer optimizations, memory and precision management, and advanced parallelization across multi-node GPU clusters.
Technological Innovation: Proactively implement cutting-edge optimization techniques to keep DigitalOcean at the forefront of the Gen AI landscape. Some examples of projects you may work on:

Improving batch size performance using AMD's AITER library for AMD MI355X - identify and tune AITER's CK (composable kernel) or ASK (assembly) to optimize FP8 / BF16
Identify kernel fusion opportunities for GLM-5 kernels for different layers of the Transformer block (FlashAttention, RMS Norm)
Tune expert gateway router kernels for MoE models like Qwen3-235B, DeepSeek V3, GLM-5 etc

Hardware & Ecosystem Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton), advising on hardware procurement and software integration.
Precision Optimization: Develop and deploy state-of-the-art quantization techniques (FP8, INT8, and experimental FP4) to double throughput without losing accuracy.
Technical Mentorship: Lead by example through high-quality code and design reviews, elevating the technical bar for the team without the administrative overhead of direct management.
Strategic Collaboration: Partner with Product Management and TPMs to translate "theoretical hardware limits" into "shippable product features," ensuring our platform is both powerful and developer-friendly.
Community Leadership: Maintain a strong presence in the GPU infrastructure and model performance optimization communities, contributing to and integrating the best of open-source AI.

What You'll Bring to DigitalOcean:

Technical Depth: 5+ years of experience in high-performance computing or AI infrastructure, with a proven track record of solving compute utilization and memory bandwidth bottlenecks.
Gen AI Literacy: Deep familiarity with the Gen AI (LLM, VLM, LMM) landscape, including the specific quirks and architectural requirements of major model families.
Optimization Expert: Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments.
Hardware Fluency: Comprehensive understanding of NVIDIA and AMD GPU architectures and their respective software ecosystems (CUDA, ROCm, etc.).
Open Source Mastery: Extensive experience integrating, building with, and contributing to open-source software projects.
Systems Design: Excellent system design skills, particularly related to low-level GPU programming - optimization, memory access patterns, and parallel execution.
Leadership through Influence: Experience acting as a technical lead, driving design and delivery through cross-functional alignment and expert-level delegation.
Low-Level Mastery: Deep understanding of GPU architectures (SMs, Warp scheduling, Tensor Cores).
The Toolkit: Expert-level Triton or CUDA. If you've contributed to the Triton compiler or wrote custom CUDA kernels for a major LLM, we want you.

Compensation Range:

$191,200 - $239,000

*This is a remote role

JR: 2026-7625

#LI-Remote

Why You'll Like Working for DigitalOcean

We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91116063
Position Id: a08791fa2e43efb49b60ac492345aaf7
Posted 1 day ago

Systems Research Engineer Intern - GPU Programming (Fall 2026)

San Francisco, California

•

Today

About The Role As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and

Full-time

USD 58.00 - 63.00 per hour

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Staff Engineer, Inference Optimizations

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Staff Engineer, Inference Optimizations

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